In order to improve the reconstruction accuracy of magnetic resonance imaging (MRI), an accurate natural image compressed sensing (CS) reconstruction network is proposed, which combines the advantages of model-based a...
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The study presents the economic feasibility assessment of converting the produced biogas from water hyacinth biomass into electricity. Approximately, 0.3793 m3CH4/kgVS was generated from the water hyacinth biomass. Th...
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The ability to capture long-range contextual information is crucial for image inpainting networks when dealing with complex semantic scenes and large areas of damage. Therefore, Transformers and frequency-based learni...
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Understanding and clarifying the evolution of microstructure and performance of Al-Zr-Sc alloy wires during processing paths is a crucial issue in developing heat-resistant conductors with high strength and high elect...
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Understanding and clarifying the evolution of microstructure and performance of Al-Zr-Sc alloy wires during processing paths is a crucial issue in developing heat-resistant conductors with high strength and high electrical conductivity(EC).In this study,the microstructure evolution and corresponding performance changes of Al-0.2Zr-0.06Sc alloy wires produced by three processing paths are *** indicate that ageing treatment+hot extrusion+cold drawing processing path can produce the highest strength Al-Zr-Sc wires attributed to favorable interactions among precipitation strengthening of Al_(3)(Zr,Sc)phases,grain boundary strengthening and dislocation *** EC is attained by the hot extrusion+ageing treatment+cold drawing processing path,which reveals the importance of dynamic precipitation of Al_(3)Sc phases during hot extrusion and further precipitation of solute atoms during ageing treatment for improving the *** processing path using hot extrusion+cold drawing+ageing treatment achieves the highest EC of the Al-Zr-Sc wire,but the strength decreases significantly due to the loss of dislocation ***,the pinning effect of Al_(3)Sc and Al_(3)(Zr,Sc)ensures good heat resistance of Al-Zr-Sc *** results provide guidance for the process design of Al-Zr-Sc wires with variable combinations of strength and EC.
Sensitivity encoding (SENSE) is a parallel magnetic resonance imaging (MRI) reconstruction model by utilizing the sensitivity information of receiver coils to achieve image reconstruction. The existing SENSE-based rec...
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Wearable technology is expanding rapidly in recent year. It is used in many applications in various domains, including affective computing. Affective computing is all about understanding and responding to human emotio...
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In the era of advanced machine learning techniques,the development of accurate predictive models for complex medical conditions,such as thyroid cancer,has shown remarkable *** predictivemodels for thyroid cancer enhan...
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In the era of advanced machine learning techniques,the development of accurate predictive models for complex medical conditions,such as thyroid cancer,has shown remarkable *** predictivemodels for thyroid cancer enhance early detection,improve resource allocation,and reduce ***,the widespread adoption of these models in clinical practice demands predictive performance along with interpretability and *** paper proposes a novel association-rule based feature-integratedmachine learning model which shows better classification and prediction accuracy than present *** study also focuses on the application of SHapley Additive exPlanations(SHAP)values as a powerful tool for explaining thyroid cancer prediction *** the proposed method,the association-rule based feature integration framework identifies frequently occurring attribute combinations in the *** original dataset is used in trainingmachine learning models,and further used in generating SHAP values *** the next phase,the dataset is integrated with the dominant feature sets identified through association-rule based *** new integrated dataset is used in re-training the machine learning *** new SHAP values generated from these models help in validating the contributions of feature sets in predicting *** conventional machine learning models lack interpretability,which can hinder their integration into clinical decision-making *** this study,the SHAP values are introduced along with association-rule based feature integration as a comprehensive framework for understanding the contributions of feature sets inmodelling the *** study discusses the importance of reliable predictive models for early diagnosis of thyroid cancer,and a validation framework of *** proposed model shows an accuracy of 93.48%.Performance metrics such as precision,recall,F1-score,and the area un
In telemedicine applications, it is crucial to ensure the authentication, confidentiality, and privacy of medical data due to its sensitive nature and the importance of the patient information it contains. Communicati...
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In telemedicine applications, it is crucial to ensure the authentication, confidentiality, and privacy of medical data due to its sensitive nature and the importance of the patient information it contains. Communication through open networks is insecure and has many vulnerabilities, making it susceptible to unauthorized access and misuse. Encryption models are used to secure medical data from unauthorized access. In this work, we propose a bit-level encryption model having three phases: preprocessing, confusion, and diffusion. This model is designed for different types of medical data including patient information, clinical data, medical signals, and images of different modalities. Also, the proposed model is effectively implemented for grayscale and color images with varying aspect ratios. Preprocessing has been applied based on the type of medical data. A random permutation has been used to scramble the data values to remove the correlation, and multilevel chaotic maps are fused with the cyclic redundancy check method. A circular shift is used in the diffusion phase to increase randomness and security, providing protection against potential attacks. The CRC method is further used at the receiver side for error detection. The performance efficiency of the proposed encryption model is proved in terms of histogram analysis, information entropy, correlation analysis, signal-to-noise ratio, peak signal-to-noise ratio, number of pixels changing rate, and unified average changing intensity. The proposed bit-level encryption model therefore achieves information entropy values ranging from 7.9669 to 8.000, which is close to the desired value of 8. Correlation coefficient values of the encrypted data approach to zero or are negative, indicating minimal correlation in encrypted data. Resistance against differential attacks is demonstrated by NPCR and UACI values exceeding 0.9960 and 0.3340, respectively. The key space of the proposed model is 1096, which is substantially mor
The increasing number of electronic transactions on the Internet has given rise to the design of recommendation systems. The main objective of these systems is to give recommendations to the users about the items (i.e...
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The challenge of bankruptcy prediction, critical for averting financial sector losses, is amplified by the prevalence of imbalanced datasets, which often skew prediction models. Addressing this, our study introduces t...
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